· 5 min read
How Tamaton's Search Reads Your Files Before You Ask
A concrete look at building RAG over your own email, docs, and drive — and why retrieval quality, not model size, decides whether AI knowledge work is actually useful.
All#ai#ai-agents#ai-productivity#applied-ai#automation#calendar#context-switching#deep-work#documents#email#engineering#engineering-leadership#invisible-ai#knowledge-work#llm-evaluation#product-updates#productivity#prompt-engineering#remote-work#search#security#spreadsheets#startups#storage#tamaton#unified-workspace#workflow#workflows
· 5 min read
The Inbox Is the Real Agent Benchmark
Coding demos are graded by a test suite. Email is graded by your boss, your customer, and your calendar. Here's why the inbox is the hardest honest test of an AI agent.
· 5 min read
Reason, Plan, Act — Then What? Evaluating Agents That Do Work
Reasoning and planning demos are easy. Proving a multi-step agent actually finished the job — correctly, safely, once — is the unsolved part. Here's how to measure it.
· 5 min read
Stop Calling It an Agent: A Working Taxonomy for 2026
"Agent" now means everything from a system prompt to a six-hour autonomous process. Here's a five-tier taxonomy based on autonomy, state, and blast radius — and why most agents on sale are tier one.
· 5 min read
Fine-Tuning vs. In-Context Learning: When to Bother
Most teams reach for fine-tuning when a decent retrieval pipeline and a tight prompt would have been cheaper, faster, and far easier to change tomorrow. Here's how to tell the difference.
· 5 min read
Your Inbox Is the Best RAG Corpus You Already Own
Email is a timestamped, attributed archive of how your org actually decides things. Here's how to make it a retrieval corpus without leaking data or resurfacing stale threads.
· 4 min read
Most AI Productivity Tools Don't Save Time. Here's the Test.
A defensible framework for measuring whether an AI tool actually returns hours — including verification overhead, context-switching, and the trust tax nobody counts.
· 5 min read
What AI Agents Can Actually Delegate (and What They Shouldn't)
A practical taxonomy of AI agents delegation built on reversibility, verifiability, and blast radius — five tiers from 'let it run' to 'don't, ever.'
· 5 min read
Give Your Tamaton Agent a Job Description, Not a Prompt
Stop writing clever prompts and start writing employment contracts. A concrete walkthrough of scoping a Tamaton custom agent with permissions, escalation thresholds, and an audit trail.
· 4 min read
Federated LLMs: Why Your Data Doesn't Have to Leave the Building
Federated training lets models learn across organizations without pooling sensitive data. Here's what that shift means for privacy-preserving AI and knowledge work.
· 5 min read
Your Agent Is Only as Smart as the Context You Feed It
"Humans lead agent success" is a polite way of saying context engineering. Here's why a unified workspace beats a pile of disconnected tools as RAG substrate.
· 4 min read
Stop Vibe-Checking Your AI: Build a 50-Case Eval Set
Public benchmarks won't tell you if a model can triage your inbox or reconcile your spreadsheet. Here's how to build a private, brutally specific eval set in an afternoon.
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